Let’s define some vectors which can be used for demonstrations:
manyNumbers <- sample( 1:1000, 20 )
manyNumbers
[1] 159 148 404 361 489 714 537 934 505 127 584 401 678 423 386 390 544 428 133 552
manyNumbersWithNA <- sample( c( NA, NA, NA, manyNumbers ) )
manyNumbersWithNA
[1] NA 423 361 678 714 584 544 401 489 159 390 133 505 934 NA 127 537 148 552 NA 428 404 386
duplicatedNumbers <- sample( 1:5, 10, replace = TRUE )
duplicatedNumbers
[1] 1 1 3 1 3 5 3 5 3 2
letters
[1] "a" "b" "c" "d" "e" "f" "g" "h" "i" "j" "k" "l" "m" "n" "o" "p" "q" "r" "s" "t" "u" "v" "w" "x" "y" "z"
LETTERS
[1] "A" "B" "C" "D" "E" "F" "G" "H" "I" "J" "K" "L" "M" "N" "O" "P" "Q" "R" "S" "T" "U" "V" "W" "X" "Y" "Z"
mixedLetters <- c( sample( letters, 5 ), sample( LETTERS, 5 ) )
mixedLetters
[1] "o" "b" "a" "v" "j" "R" "Q" "P" "K" "O"
manyNumbersWithNA instead of manyNumbers.all( manyNumbers <= 1000 )
[1] TRUE
all( manyNumbers <= 500 )
[1] FALSE
any( manyNumbers > 1000 )
[1] FALSE
any( manyNumbers > 500 )
[1] TRUE
all( !is.na( manyNumbers ) )
[1] TRUE
any( is.na( manyNumbers ) )
[1] FALSE
Input: logical vector Output: vector of numbers (positions)
which( manyNumbers > 900 )
[1] 8
which( manyNumbersWithNA > 900 )
[1] 14
which( is.na( manyNumbersWithNA ) )
[1] 1 15 20
manyNumbers[ manyNumbers > 900 ] # indexing by logical vector
[1] 934
manyNumbers[ which( manyNumbers > 900 ) ] # indexing by positions
[1] 934
somePositions <- which( manyNumbers > 900 )
manyNumbers[ somePositions ]
[1] 934
"A" %in% LETTERS
[1] TRUE
c( "X", "Y", "Z" ) %in% LETTERS
[1] TRUE TRUE TRUE
all( c( "X", "Y", "Z" ) %in% LETTERS )
[1] TRUE
all( mixedLetters %in% LETTERS )
[1] FALSE
any( mixedLetters %in% LETTERS )
[1] TRUE
mixedLetters[ mixedLetters %in% LETTERS ]
[1] "R" "Q" "P" "K" "O"
mixedLetters[ !( mixedLetters %in% LETTERS ) ]
[1] "o" "b" "a" "v" "j"
manyNumbers %in% 300:600
[1] FALSE FALSE TRUE TRUE TRUE FALSE TRUE FALSE TRUE FALSE TRUE TRUE FALSE TRUE TRUE TRUE TRUE
[18] TRUE FALSE TRUE
which( manyNumbers %in% 300:600 )
[1] 3 4 5 7 9 11 12 14 15 16 17 18 20
sum( manyNumbers %in% 300:600 )
[1] 13
NAsif_else( manyNumbersWithNA >= 500, "large", "small" )
[1] NA "small" "small" "large" "large" "large" "large" "small" "small" "small" "small" "small" "large"
[14] "large" NA "small" "large" "small" "large" NA "small" "small" "small"
if_else( manyNumbersWithNA >= 500, "large", "small", "UNKNOWN" )
[1] "UNKNOWN" "small" "small" "large" "large" "large" "large" "small" "small" "small"
[11] "small" "small" "large" "large" "UNKNOWN" "small" "large" "small" "large" "UNKNOWN"
[21] "small" "small" "small"
# here integer 0L is needed instead of real 0.0
# manyNumbersWithNA contains integer numbers and the method complains
if_else( manyNumbersWithNA >= 500, manyNumbersWithNA, 0L )
[1] NA 0 0 678 714 584 544 0 0 0 0 0 505 934 NA 0 537 0 552 NA 0 0 0
unique( duplicatedNumbers )
[1] 1 3 5 2
unique( c( NA, duplicatedNumbers, NA ) )
[1] NA 1 3 5 2
duplicated( duplicatedNumbers )
[1] FALSE TRUE FALSE TRUE TRUE FALSE TRUE TRUE TRUE FALSE
which.max( manyNumbersWithNA )
[1] 14
manyNumbersWithNA[ which.max( manyNumbersWithNA ) ]
[1] 934
which.min( manyNumbersWithNA )
[1] 16
manyNumbersWithNA[ which.min( manyNumbersWithNA ) ]
[1] 127
range( manyNumbersWithNA, na.rm = TRUE )
[1] 127 934
manyNumbersWithNA
[1] NA 423 361 678 714 584 544 401 489 159 390 133 505 934 NA 127 537 148 552 NA 428 404 386
sort( manyNumbersWithNA )
[1] 127 133 148 159 361 386 390 401 404 423 428 489 505 537 544 552 584 678 714 934
sort( manyNumbersWithNA, na.last = TRUE )
[1] 127 133 148 159 361 386 390 401 404 423 428 489 505 537 544 552 584 678 714 934 NA NA NA
sort( manyNumbersWithNA, na.last = TRUE, decreasing = TRUE )
[1] 934 714 678 584 552 544 537 505 489 428 423 404 401 390 386 361 159 148 133 127 NA NA NA
manyNumbersWithNA[1:5]
[1] NA 423 361 678 714
order( manyNumbersWithNA[1:5] )
[1] 3 2 4 5 1
rank( manyNumbersWithNA[1:5] )
[1] 5 2 1 3 4
sort( mixedLetters )
[1] "a" "b" "j" "K" "o" "O" "P" "Q" "R" "v"
manyDuplicates <- sample( 10:15, 10, replace = TRUE )
rank( manyDuplicates )
[1] 10.0 4.0 6.0 4.0 1.5 1.5 8.0 4.0 8.0 8.0
rank( manyDuplicates, ties.method = "min" )
[1] 10 3 6 3 1 1 7 3 7 7
rank( manyDuplicates, ties.method = "random" )
[1] 10 3 6 4 1 2 7 5 8 9
v <- c( -1, -0.5, 0, 0.5, 1, rnorm( 10 ) )
v
[1] -1.0000000 -0.5000000 0.0000000 0.5000000 1.0000000 -1.3567544 -0.5357007 -1.9638927 -1.3536890
[10] 0.5531375 0.2536436 0.8945281 -1.1225877 -0.6856098 -0.1121617
round( v, 0 )
[1] -1 0 0 0 1 -1 -1 -2 -1 1 0 1 -1 -1 0
round( v, 1 )
[1] -1.0 -0.5 0.0 0.5 1.0 -1.4 -0.5 -2.0 -1.4 0.6 0.3 0.9 -1.1 -0.7 -0.1
round( v, 2 )
[1] -1.00 -0.50 0.00 0.50 1.00 -1.36 -0.54 -1.96 -1.35 0.55 0.25 0.89 -1.12 -0.69 -0.11
floor( v )
[1] -1 -1 0 0 1 -2 -1 -2 -2 0 0 0 -2 -1 -1
ceiling( v )
[1] -1 0 0 1 1 -1 0 -1 -1 1 1 1 -1 0 0
heights <- c( Amy = 166, Eve = 170, Bob = 177 )
heights
Amy Eve Bob
166 170 177
names( heights )
[1] "Amy" "Eve" "Bob"
names( heights ) <- c( "AMY", "EVE", "BOB" )
heights
AMY EVE BOB
166 170 177
heights[[ "EVE" ]]
[1] 170
expand_grid( x = c( 1:3, NA ), y = c( "a", "b" ) )
# A tibble: 8 x 2
x y
<int> <chr>
1 1 a
2 1 b
3 2 a
4 2 b
5 3 a
6 3 b
7 NA a
8 NA b
combn( c( "a", "b", "c", "d", "e" ), m = 2, simplify = TRUE )
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] "a" "a" "a" "a" "b" "b" "b" "c" "c" "d"
[2,] "b" "c" "d" "e" "c" "d" "e" "d" "e" "e"
combn( c( "a", "b", "c", "d", "e" ), m = 3, simplify = TRUE )
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] "a" "a" "a" "a" "a" "a" "b" "b" "b" "c"
[2,] "b" "b" "b" "c" "c" "d" "c" "c" "d" "d"
[3,] "c" "d" "e" "d" "e" "e" "d" "e" "e" "e"
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